An open source platform for visual-inertial navigation research.
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Updated
May 31, 2024 - C++
An open source platform for visual-inertial navigation research.
IMU + X(GNSS, 6DoF Odom) Loosely-Coupled Fusion Localization based on ESKF, IEKF, UKF(UKF/SPKF, JUKF, SVD-UKF) and MAP
Underwater Dataset for Visual-Inertial Methods and data with transitioning between multiple refractive media.
"Visual-Inertial Dataset" (RA-L'21 with ICRA'21): it contains harsh motions for VO/VIO, like pure rotation or fast rotation with various motion types.
A monocular plane-aided visual-inertial odometry
A fully-annotated, open-design dataset of autonomous and piloted high-speed flight
FLVIS: Feedback Loop Based Visual Inertial SLAM
Deep Learning for Visual-Inertial Odometry
robust visual-inertial odometry, separated from openxrlab-xrslam
Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation.
Plain cmake version for rpg_svo_pro_open (svo2.0). No ros.
OAK-D + SLAM + AprilTags for localization in FRC
A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.
Harness the power of GPU acceleration for fusing visual odometry and IMU data with an advanced Unscented Kalman Filter (UKF) implementation. Developed in C++ and utilizing CUDA, cuBLAS, and cuSOLVER, this system offers unparalleled real-time performance in state and covariance estimation for robotics and autonomous system applications.
Square-Root Robocentric Visual-Inertial Odometry with Online Spatiotemporal Calibration
Roadmap to become a Visual-SLAM developer in 2023
Collaborative Navigation Dataset
Repository for the "Vision Algorithms for Mobile Robotics" (VAMR) lecture at the "Robotics and Perception Group" at UZH (for ETH Zurich).
A CUDA reimplementation of Bundle Adjustment for VINS-Fusion
Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
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